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Dsp Notes Prepared DSP NOTES PREPARED BY Ch.Ganapathy Reddy Professor & HOD, ECE Shaikpet, Hyderabad-08 Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 1 DIGITAL SIGNAL PROCESSING A signal is defined as any physical quantity that varies with time, space or another independent variable. A system is defined as a physical device that performs an operation on a signal. System is characterized by the type of operation that performs on the signal. Such operations are referred to as signal processing. Advantages of DSP 1. A digital programmable system allows flexibility in reconfiguring the digital signal processing operations by changing the program. In analog redesign of hardware is required. 2. In digital accuracy depends on word length, floating Vs fixed point arithmetic etc. In analog depends on components. 3. Can be stored on disk. 4. It is very difficult to perform precise mathematical operations on signals in analog form but these operations can be routinely implemented on a digital computer using software. 5. Cheaper to implement. 6. Small size. 7. Several filters need several boards in analog, whereas in digital same DSP processor is used for many filters. Disadvantages of DSP 1. When analog signal is changing very fast, it is difficult to convert digital form .(beyond 100KHz range) 2. w=1/2 Sampling rate. 3. Finite word length problems. 4. When the signal is weak, within a few tenths of millivolts, we cannot amplify the signal after it is digitized. 5. DSP hardware is more expensive than general purpose microprocessors & micro controllers. Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 2 6. Dedicated DSP can do better than general purpose DSP. Applications of DSP 1. Filtering. 2. Speech synthesis in which white noise (all frequency components present to the same level) is filtered on a selective frequency basis in order to get an audio signal. 3. Speech compression and expansion for use in radio voice communication. 4. Speech recognition. 5. Signal analysis. 6. Image processing: filtering, edge effects, enhancement. 7. PCM used in telephone communication. 8. High speed MODEM data communication using pulse modulation systems such as FSK, QAM etc. MODEM transmits high speed (1200-19200 bits per second) over a band limited (3-4 KHz) analog telephone wire line. 9. Wave form generation. Classification of Signals I. Based on Variables: 1. f(t)=5t : single variable 2. f(x,y)=2x+3y : two variables 3. S1= A Sin(wt) : real valued signal jwt 4. S2 = A e : A Cos(wt)+j A Sin(wt) : Complex valued signal S1(t) 5. S4(t)= S2(t) : Multichannel signal S3(t) Ex: due to earth quake, ground acceleration recorder Ir(x, y,t) 6. I(x,y,t)= Ig(x, y,t) multidimensional Ib(x, y,t) II. Based on Representation: Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 3 III. Based on duration. 1. right sided: x(n)=0 for n<N 2. left sided :x(n)=0 for n>N 3. causal : x(n)=0 for n<0 4. Anti causal : x(n)=0 for n 0 5. Non causal : x(n)=0 for n >N IV. Based on the Shape. 1. (n)=0 n 0 =1 n=0 2. u (n) =1 n 0 =0 n<0 Arbitrary sequence can be represented as a sum of scaled, delayed impulses. Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 4 P (n) = a-3 (n+3) +a1 (u-1) +a2 (u-2) +a7 (u-7) Or x(n) = x(k) (n k) k n u(n) = (k) = (n) + (n-1)+ (n-2)….. k = (n k) k0 3.Discrete pulse signals. Rect (n/2N) =1 n N = 0 else where. 5.Tri (n/N) = 1- n /N N = 0 else where. 1. Sinc (n/N)= Sa(n /N) = Sin(n /N) / (n /N), Sinc(0)=1 Sinc (n/N) =0 at n=kN, k= 1, 2… Sinc (n) = (n) for N=1; (Sin (n ) / n =1= (n)) 6.Exponential Sequence x (n) = A n If A & are real numbers, then the sequence is real. If 0< <1 and A is +ve, then sequence values are +ve and decreases with increasing n. For -1< <0, the sequence values alternate in sign but again decreases in magnitude with increasing n. If >1, then the sequences grows in magnitude as n increases. 7.Sinusoidal Sequence x(n) = A Cos(won+ ) for all n 8.Complex exponential sequence Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 5 If = ejwo j A = A e j n jwon x(n) = e e n n = Cos(won+ ) + j Sin(won+ ) If >1, the sequence oscillates with exponentially growing envelope. If <1, the sequence oscillates with exponentially decreasing envelope. So when discussing complex exponential signals of the form x(n)= A ejwon or real sinusoidal signals of the form x(n)= A Cos(won+ ) , we need only consider frequencies in a frequency internal of length 2 such as < Wo < or 0 Wo<2 . V. Deterministic (x (t) = t x (t) = A Sin(wt)) & Non-deterministic Signals. (Ex: Thermal noise.) VI. Periodic & non periodic based on repetition. VII. Power & Energy Signals Energy signal: E = finite, P=0 Signal with finite energy is called energy signal. Energy signal have zero signal power, since averaging finite energy over infinite time. All time limited signals of finite amplitude are energy signals. Ex: one sided or two sided decaying. Damped exponentials, damped sinusoidal. x(t) is an energy signal if it is finite valued and x2 (t) decays to zero fasten than 1 t as t . Power signal: E = , P 0, P Ex: All periodic waveforms n Neither energy nor power: E= , P=0 Ex: 1/ t t 1 E= , P= , Ex: t VIII. Based on Symmetry 1. Even x(n)=xe(n)+xo(n) 2. Odd x(-n)=xe(-n)+xo(-n) 3. Hidden x(-n)=xe(n)-xo(n) 1 4. Half-wave symmetry. xe(n)= [x(n)+x(-n)] 2 Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 6 1 xo(n)= [x(n)-x(-n)] 2 Signal Classification by duration & Area. a. Finite duration: time limited. b. Semi-infinite extent: right sided, if they are zero for t < where = finite c. Left sided: zero for t > Piecewise continuous: possess different expressions over different intervals. Continuous: defined by single expressions for all time. x(t) = sin(t) Periodic: xp (t) = xp (t nT) 1 T For periodic signals P = x(t) 2 dt T 0 X rms = P For non periodic 1 T P = Lt x(t) 2 dt To 0 To Xavg = Lt x(t)dt 0 2 x(t) = A cos( 2 fo t + ) P=0.5 A x(t) = A e j( 2 fo t + ) P=A2 Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 7 1 1 E= A2 b E = A2 b E = A2 b 2 3 Q. 1 e - t dt = 0 Q. 1 1 Ex = A2 0.5T + (-A)2 0.5T = 0.5 A2 T 2 2 Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 8 Px = 0.5 A2 Q. 1 1 Ey = [ A2 0.5T] 2 = A2 T 3 3 Py = A2 x(t) = A ejwt is periodic 1 T Px = x(t) 2 dt = A2 T 0 x(2t -6 ): compressed by 2 and shifted right by 3 OR shifted by 6 and compressed by 2. x(1-t): fold x(t) & shift right by 1 OR shift right and fold. x(0.5t +0.5) Advance by 0.5 & stretched by 2 OR stretched by 2 & advance by 1. (t 2) t 2 y (t) = 2 x [- ] = 2 x[ ] 2 x( t + ) ; 5 + =-1; - + =1 => = -1/3 3 3 3 ; = 2/3 Area of symmetric signals over symmetric limits (- , ) Odd symmetry: x0 (t) dt =0 Even symmetry: xe (t) dt = 2 xe (t) dt 0 Xe (t) +Ye (t): even symmetry. Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 9 Xe (t) Ye (t): even symmetry. 1 2 Xo (t) +Yo (t): odd symmetry. Xo (t) Xo (t): even symmetry. Xe (t) +Yo (t): no symmetry. Xe (t) Yo (t): odd symmetry. Xe(n)= [x(n)+x(-n)] Xo (n) = [x (n)-x (-n)] Area of half-wave symmetry signal always zero. Half wave symmetry applicable only for periodic signal. F0 = GCD ( f1,f2) T = LCM (T1, T2) Y(t) = x1(t) + x2(t) Py= Px1+Px2 Y(t)rms = Py U(0) = 0.5 is called as Heaviside unit step. X(t) = Sin(t) Sin( t) = 0.5 cos (1- )t – 0.5 cos (1+ ) t W1=1- W2=1+ almost periodic OR non periodic. 2 2 Px = 0.5[0.5 +0.5 ] =0.25 W Area of any sinc or Sinc 2 equals area of triangle ABC inscribed within the main lobe. 1 2 Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 10 Even though the sinc function is square integrable ( an energy signal) , it is not absolutely integrable( because it does not decay to zero faster than ) (t) = 0 t 0 = t=0 ( )d = 1 An impulse is a tall narrow spike with finite area and infinite energy. The area of impulse A (t) equals A and is called its strength. How ever its hight at t=0 is . -t = 2 (t) – 2e u(t) 2 e-t (t) = 2 (t) 1 [ [t- ]] = (t ) 1 t 2 2 I 2 = cos(2t) (2t 1)dt = cos(2t)0.5 (t 0.5)dt = 0.5 cos(2 t) at t=-0.5 = -0.5 4 4 x1(t) = x(t) (t-kts ) = x(kts) (t-kts) k k Ch Ganapathy Reddy, Prof and HOD, ECE, GNITS id:[email protected],9052344333 11 x1(t) is not periodic.
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